Randomization inference in shift share designs with an application in banking
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional do FGV (FGV Repositório Digital) |
Texto Completo: | https://hdl.handle.net/10438/33329 |
Resumo: | This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy. |
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Oliveira, Raoni Ribeiro Aredes deEscolas::EESPPossebom, Vitor AugustoSant'Anna, Pedro H. C. G.Ferman, BrunoMata, Daniel da2023-03-14T15:20:17Z2023-03-14T15:20:17Z2023-03-06https://hdl.handle.net/10438/33329This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy.Esta Dissertação de Mestrado é composta de duas partes. A primeira, apresentada no Capítulo 1, é uma contribuição teórica em econometria para Shift-Share Designs, baseada no trabalho feito em conjunto com Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (veja a referência Alvarez et al., 2022). Ela mostra que, escolhendo uma estatística adequadamente estudentizada para realizar Inferência por Randomização, nós somos capazes de (i) controlar o tamanho do teste em amostras finitas sob condições relativamente fortes, como efeitos homogêneos de tratamento e distribuição conhecida dos choques, e (ii) controlar o tamanho do teste assintoticamente sob condiçõesmenos exigentes, como heterogeneidade dos efeitos de tratamento e distribuição dos choques usada nas simulações (randomização) "bem comportados", ainda que essa última seja diferente da distribuição verdadeira do processo gerador de dados. A segunda parte, no Capítulo 2, é uma aplicação empírica dessa técnica à expansão da rede física de agências bancárias no Brasil durante o boom de commodities dos anos 2000 e 2010. Tenta-se medir até que ponto o aumento do número de agências foi uma resposta à maior atividade econômica. Trata-se uma pergunta interessante pois, à época, essa rede física foi um vetor de inclusão financeira. Entender até que ponto isso foi estimulado por um choque exógeno de demanda pode ser informativo para políticas públicas futuras.engShift-share designsRandomization inferenceBrazilBank branch networkInferênciaRede bancáriaAgênciasEconomiaEconometriaEstatística matemáticaBancos - BrasilDesenvolvimento econômicoRandomization inference in shift share designs with an application in bankinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVORIGINALssri_raoni_2023_ABNT_v4.pdfssri_raoni_2023_ABNT_v4.pdfPDFapplication/pdf879881https://repositorio.fgv.br/bitstreams/e9c42aa7-ce00-4065-8156-80b3092366d2/downloadd74449210f9ee604dfbd67976d02be8cMD51LICENSElicense.txtlicense.txttext/plain; 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|
dc.title.eng.fl_str_mv |
Randomization inference in shift share designs with an application in banking |
title |
Randomization inference in shift share designs with an application in banking |
spellingShingle |
Randomization inference in shift share designs with an application in banking Oliveira, Raoni Ribeiro Aredes de Shift-share designs Randomization inference Brazil Bank branch network Inferência Rede bancária Agências Economia Econometria Estatística matemática Bancos - Brasil Desenvolvimento econômico |
title_short |
Randomization inference in shift share designs with an application in banking |
title_full |
Randomization inference in shift share designs with an application in banking |
title_fullStr |
Randomization inference in shift share designs with an application in banking |
title_full_unstemmed |
Randomization inference in shift share designs with an application in banking |
title_sort |
Randomization inference in shift share designs with an application in banking |
author |
Oliveira, Raoni Ribeiro Aredes de |
author_facet |
Oliveira, Raoni Ribeiro Aredes de |
author_role |
author |
dc.contributor.unidadefgv.por.fl_str_mv |
Escolas::EESP |
dc.contributor.member.none.fl_str_mv |
Possebom, Vitor Augusto Sant'Anna, Pedro H. C. G. |
dc.contributor.author.fl_str_mv |
Oliveira, Raoni Ribeiro Aredes de |
dc.contributor.advisor1.fl_str_mv |
Ferman, Bruno Mata, Daniel da |
contributor_str_mv |
Ferman, Bruno Mata, Daniel da |
dc.subject.eng.fl_str_mv |
Shift-share designs Randomization inference Brazil Bank branch network |
topic |
Shift-share designs Randomization inference Brazil Bank branch network Inferência Rede bancária Agências Economia Econometria Estatística matemática Bancos - Brasil Desenvolvimento econômico |
dc.subject.por.fl_str_mv |
Inferência Rede bancária Agências |
dc.subject.area.por.fl_str_mv |
Economia |
dc.subject.bibliodata.por.fl_str_mv |
Econometria Estatística matemática Bancos - Brasil Desenvolvimento econômico |
description |
This Master Thesis is comprised of two parts. The first one, presented in Chapter 1, is a theoretical advance in econometrics for Shift-share Designs, based on joint work with Luis Alvarez and Bruno Ferman, "Randomization Inference Tests for Shift-Share Designs" (see the reference Alvarez et al., 2022). It shows that, by choosing a properly studentized statistic for performing Randomization Inference, we are able to (i) control size in finite samples under relatively strong hypotheses, such as homogeneous treatment effects and known assignment process, and (ii) control size asymptotically under milder hypotheses, such as a "well-behaved" treatment heterogeneity and randomization distribution, even if it is different from the original assignment process. The second part, in Chapter 2, is an empirical application of this technique to the expansion of the physical bank network in Brazil during the commodity boom of the 2000's and 2010's. It seeks to measure to what extent the increase in the number of branches in the period was a response to greater economic activity. This is of interest because, at the time, the physical network was a vector of financial inclusion. Understanding the extent to which this was spurred by exogenous demand shocks may be informative for future policy. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-03-14T15:20:17Z |
dc.date.available.fl_str_mv |
2023-03-14T15:20:17Z |
dc.date.issued.fl_str_mv |
2023-03-06 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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https://hdl.handle.net/10438/33329 |
dc.language.iso.fl_str_mv |
eng |
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eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
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openAccess |
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